Update app.py

app.py

@@ -13,14 +13,14 @@ model_default = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
 def get_lora_sd_pipeline(
-    ckpt_dir='./lora_man_animestyle',
+    lora_dir='./lora_man_animestyle',
     base_model_name_or_path=None, 
     dtype=torch.float16, 
     adapter_name="default"
     ):
 
-    unet_sub_dir = os.path.join(ckpt_dir, "unet")
-    text_encoder_sub_dir = os.path.join(ckpt_dir, "text_encoder")
+    unet_sub_dir = os.path.join(lora_dir, "unet")
+    text_encoder_sub_dir = os.path.join(lora_dir, "text_encoder")
     
     if os.path.exists(text_encoder_sub_dir) and base_model_name_or_path is None:
         config = LoraConfig.from_pretrained(text_encoder_sub_dir)
@@ -56,7 +56,7 @@ def align_embeddings(prompt_embeds, negative_prompt_embeds):
     return torch.nn.functional.pad(prompt_embeds, (0, 0, 0, max_length - prompt_embeds.shape[1])), \
            torch.nn.functional.pad(negative_prompt_embeds, (0, 0, 0, max_length - negative_prompt_embeds.shape[1]))
 
-pipe_default = get_lora_sd_pipeline(ckpt_dir='./lora_man_animestyle', base_model_name_or_path=model_default, dtype=torch_dtype).to(device)
+pipe_default = get_lora_sd_pipeline(lora_dir='./lora_man_animestyle', base_model_name_or_path=model_default, dtype=torch_dtype).to(device)
 
 def infer(
     prompt, 
@@ -67,7 +67,7 @@ def infer(
     model='stable-diffusion-v1-5/stable-diffusion-v1-5', 
     seed=4, 
     guidance_scale=7.5, 
-    lora_scale=0.05,
+    lora_scale=0.5,
     progress=gr.Progress(track_tqdm=True)
     ):